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Model-based State-of-energy Estimation of Lithium-ion Batteries in Electric Vehicles

AbstractWith the increasing application of lithium-ion batteries, the function of battery management system (BMS) comes to be more sophisticated. The state-of-energy (SOE) of lithium-ion batteries is a critical index for energy optimization and management in electric vehicles. The conventional power integral methods are easy to cause accumulated error due to current or voltage drift of sensors. Therefore the EKF method is employed in this study. A data-driven model is established to describe the relationship between the open-circuit voltage (OCV) and SOE based on the experimental data of a Li(Ni1/3Co1/3Mn1/3)O2 battery. The dynamic urban driving schedule of Wuhui city in China has been conducted on the lithium-ion battery to verify the accuracy of the proposed method. The results show that accurate SOE estimation results can be obtained by the proposed method.
- University of Science and Technology of China China (People's Republic of)
EKF., State-of-energy, Battery modeling, Electric vehicle
EKF., State-of-energy, Battery modeling, Electric vehicle
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).28 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
